Human prophylaxis-driven cooperative spreading between information and epidemics in duplex networks.

IF 2.7 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2025-03-01 DOI:10.1063/5.0254726
Congying Liu, Xiaoqun Wu, Xiaoyang Liu, Ling Lei, Junchan Zhao
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引用次数: 0

Abstract

Human behaviors play a crucial role in the intertwined dynamics of information diffusion and epidemic spreading. In turn, the spread of information and epidemics also affects individual behavioral changes. Understanding how information and epidemics propagate when individuals make coordinated decisions is essential to designing practicable control policies. To delve into this, we modify the unaware-aware-unaware susceptible-infected-susceptible (UAU-SIS) model by a two-strategy game-theory dilemma and explore how individual protective behaviors drive the interaction between information diffusion and epidemic spreading. Our theoretical analysis reveals that at the onset of an epidemic, individuals will not take any preventive measures, with the epidemic threshold being determined primarily by the topological structure of the epidemic layer. Extensive simulations help us explore the emergence of protective behaviors. A key finding is the existence of a crucial protection threshold, beyond which aware individuals begin to adopt preventive measures. Furthermore, our findings suggest that the high recovery rate or cost associated with contracting the disease, coupled with the poor failure rate of preventive measures or the low forgotten rate, leads to a significant number of aware individuals participating in self-protection, curbing the spread of epidemics. Moreover, even though individual protective decisions evolve in the information layer, the topology of the epidemic layer profoundly impacts both information diffusion and epidemic spreading. This work offers a new insight into the intertwined processes between information diffusion and epidemic spreading driven by human behaviors, which could help decision-makers gain some viable approaches to intervening in diseases.

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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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